Here is my problem.
I have a set of data that are made of 4 parameters : x, y, dx and dy
I'd like to classify this set the following way : put together all (x,y) that
have similar (dx, dy).
I've had a look at Gaussian mixture models implementation in scikit, and it
seems to be what I need. But the examples i've found here :
http://scikit-learn.sourceforge.net/0.5/auto_examples/gmm/plot_gmm.html#
only fit y vs x.
In my case for instance, all my (x,y) would be in red, but some of the (dx,
dy) would point towards you, and some would point away from you, and I'd like
to sort the data according to this "parameter": the pointing direction.
How can I modify the example so that it fits 2 dims, keeping the first two as
input ? And does it make sense to use this kind of method, my knowledge in
statistics is quite limited.
Many thanks.
Éric
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Un clavier azerty en vaut deux
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Éric Depagne eric@depagne.org